Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Fanhua Ming"'
Autor:
Binglu Huang, Shan Tian, Na Zhan, Jingjing Ma, Zhiwei Huang, Chukang Zhang, Hao Zhang, Fanhua Ming, Fei Liao, Mengyao Ji, Jixiang Zhang, Yinghui Liu, Pengzhan He, Beiying Deng, Jiaming Hu, Weiguo Dong
Publikováno v:
EBioMedicine, Vol 73, Iss , Pp 103631- (2021)
Background: To reduce the high incidence and mortality of gastric cancer (GC), we aimed to develop deep learning-based models to assist in predicting the diagnosis and overall survival (OS) of GC patients using pathological images. Methods: 2333 hema
Externí odkaz:
https://doaj.org/article/822ff56ef46a4f0883849a9da9e5a389
Autor:
Huiying Shi, Zhen Ding, Hang Zhang, Hao Zhang, Shuxin Tian, Kun Zhang, Sicheng Cai, Fanhua Ming, Xiaoping Xie, Jun Liu, Rong Lin
Publikováno v:
Endoscopy. 55:44-51
Background Further development of deep learning-based artificial intelligence (AI) technology to automatically diagnose multiple abnormalities in small-bowel capsule endoscopy (SBCE) videos is necessary. We aimed to develop an AI model, to compare it
Publikováno v:
Gastroenterology Report. 11
Background Chromoendoscopy has not been fully integrated into capsule endoscopy. This study aimded to develop and validate a novel intelligent chromo capsule endoscope (ICCE). Methods The ICCE has two modes: a white-light imaging (WLI) mode and an in
Autor:
Jingjing Ma, Fei Liao, Weiguo Dong, Mengyao Ji, Chukang Zhang, Yinghui Liu, Hao Zhang, Shan Tian, Pengzhan He, Beiying Deng, Jixiang Zhang, Na Zhan, Jiaming Hu, Binglu Huang, Zhiwei Huang, Fanhua Ming
Publikováno v:
EBioMedicine
EBioMedicine, Vol 73, Iss, Pp 103631-(2021)
EBioMedicine, Vol 73, Iss, Pp 103631-(2021)
Background: To reduce the high incidence and mortality of gastric cancer (GC), we aimed to develop deep learning-based models to assist in predicting the diagnosis and overall survival (OS) of GC patients using pathological images. Methods: 2333 hema
Autor:
Zhen Ding, Weijun Wang, Kun Zhang, Fanhua Ming, Tianyi Yangdai, Tao Xu, Huiying Shi, Yuhui Bao, Hailing Yao, Hangyu Peng, Chaoqun Han, Weiwei Jiang, Jun Liu, Xiaohua Hou, Rong Lin
Publikováno v:
Gut; Dec2021, Vol. 70 Issue 12, p2297-2306, 10p